Optimizing end user QoS in heterogeneous network environments using reputation and prediction

Abstract

Telecommunication consumers are fueling a demand for mobile devices that are rapidly increasing in their capability to provide a wider range of services. These services in turn are consuming more bandwidth and require richer quality of service (QoS) in order to ensure a good end user experience when performing activities such as streaming video content or facilitating voice over IP. As a result, network providers are expanding and improving their coverage area while technology to establish Wi-Fi hotspots is becoming more accessible to every day users. This combination of increase in demand and accessibility, coupled with users' ever-increasing expectations for high quality service presents a growing need to seamlessly optimize the use of the overlaid heterogeneous networks in urban areas to maximize the end user experience via the use of a vertical handover mechanism (VHO). Grey systems theory has been used in a wide range of systems including economic, financial, transportation, and military to accurately forecast time series based on limited information. In this paper, we build on a novel reputation-based VHO decision rating system by proposing the use of the grey model first-order one variable, GM(1,1), in the handover decision making progress. The low complexity of the GM(1,1) model allows for a quick and efficient prediction of the future reputation score for a given network, providing deeper insight into the current state of the target network. Furthermore, simulations show that the proposed model, in comparison with the original reputation model, improves the decision capability of a mobile node and helps balance the load across the heterogeneous networks employing its strategy. © 2013 Stolojescu-Crisan and Isar; licensee Springer.